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16 diciembre 2021
Adrián González Sánchez
La realidad de la
gestión de
proyectos IA
CC BY 4.0 - Adrian Gonzalez Sanchez
CC BY 4.0 - Adrian Gonzalez Sanchez
[AI Lead Talk] La realidad de la gestión de proyectos IA
x
www.linkedin.com/in/adriangs86
https://adrian-gonzalezsanchez.medium.com
2
Vuestro amigo y vecino…
Adrián González Sánchez
Telco & IT Engineer, MSc. + MBA
Tech Executive + University Lecturer
Montreal, Canada _
CC BY 4.0 - Adrian Gonzalez Sanchez
[AI Lead Talk] La realidad de la gestión de proyectos IA
Nuestro plan hoy - AI Lead Talk
2021 AI/ML Highlights – ¿Dónde estamos?
Key Project Learnings – La realidad del día a día
Q&A
3
1
2
3
[AI Lead Talk] La realidad de la gestión de proyectos IA
CC BY 4.0 - Adrian Gonzalez Sanchez
2021 AI/ML Highlights
4
1
I. Democratization of the AI adoption is generating new opportunities for all kinds of AI professionals (tech, biz, and
hybrid profiles). I see more people with "atypical profiles" re/upskilling so they can help with new internal AI initiatives for
small and medium businesses. We are going more granular in terms of AI skills and responsibilities. Cloud-enabled /
aaS platforms are helping a lot.
II. MLOps is the key industry trend, and an organic answer to the need for a well-defined end-to-end AI/ML lifecycle. This is
also contributing to clarify tasks / micro-tasks and responsibilities. I think data and ML engineers will have a lot of fun in
2022 :) their roles are evolving very quickly, same as their importance within the adopter organizations.
III. Responsible AI is finally becoming something tangible. Main concern for AI professionals was how to actually evaluate
responsible AI factors during the analysis, implementation, and prod phases. Big companies are releasing both
commercial and open source solutions to check fairness, explicability, data bias, etc. Still a WIP but I really like what I
see from Microsoft, TensorFlow/Google, etc.
IV. The data scientist skill set is also evolving. Some of the DS/DE tasks are becoming a bit more of a "commodity" (e.g.,
initial naive approaches, model benchmarking), and technical complexity requires more and better soft skills than ever. I
have met wonderful data scientist, but my favourite ones are those who are able to explain choices and results in a very
simple way, so everyone can understand the key pieces. Superstar data scientists will bring that to the companies, and
they will become key decision influencers.
Fuente propia: https://www.linkedin.com/posts/adriangs86_ai2021-2022predictions-ai-activity-6875764835808808961-RjnI
[AI Lead Talk] La realidad de la gestión de proyectos IA
CC BY 4.0 - Adrian Gonzalez Sanchez
5
The impact of early
involvement of end-users in
designing AI solutions
1
Key Project Learnings
2
[AI Lead Talk] La realidad de la gestión de proyectos IA
CC BY 4.0 - Adrian Gonzalez Sanchez
6
The benefits of AI education for
stakeholders to facilitate
adoption and collaboration
2
Key Project Learnings
2
[AI Lead Talk] La realidad de la gestión de proyectos IA
CC BY 4.0 - Adrian Gonzalez Sanchez
7
The importance of
executive-level sponsorship
and their understanding of AI
3
Key Project Learnings
2
[AI Lead Talk] La realidad de la gestión de proyectos IA
CC BY 4.0 - Adrian Gonzalez Sanchez
8
4 The incredible power of
mission-oriented projects
for AI implementations
Key Project Learnings
2
[AI Lead Talk] La realidad de la gestión de proyectos IA
CC BY 4.0 - Adrian Gonzalez Sanchez
9
The notion of “good enough”
AI model performance to
manage expectations up-front
5
Key Project Learnings
2
[AI Lead Talk] La realidad de la gestión de proyectos IA
CC BY 4.0 - Adrian Gonzalez Sanchez
10
The trade-off between fully
automated and HITL
Human-in-the-loop systems
6
Key Project Learnings
2
[AI Lead Talk] La realidad de la gestión de proyectos IA
CC BY 4.0 - Adrian Gonzalez Sanchez
11
The necessity of using AI for
specific “narrow” tasks and
leveraging SME knowledge
7
Key Project Learnings
2
[AI Lead Talk] La realidad de la gestión de proyectos IA
CC BY 4.0 - Adrian Gonzalez Sanchez
12
The scalability of AI use cases
and their connection with
previous and future projects
8
Key Project Learnings
2
[AI Lead Talk] La realidad de la gestión de proyectos IA
CC BY 4.0 - Adrian Gonzalez Sanchez
13
The required effort for granular
AI project planning and risk
mitigation
9
Key Project Learnings
2
[AI Lead Talk] La realidad de la gestión de proyectos IA
CC BY 4.0 - Adrian Gonzalez Sanchez
14
The role of AI tooling and
infrastructure to accelerate
implementations
10
Key Project Learnings
2
[AI Lead Talk] La realidad de la gestión de proyectos IA
CC BY 4.0 - Adrian Gonzalez Sanchez
15
Mi regalo de navidad - Lecturas para gestión 360 de IA/ML
+
CC BY 4.0 - Adrian Gonzalez Sanchez
[AI Lead Talk] La realidad de la gestión de proyectos IA
16
Q&A
16 diciembre 2021
Adrian Gonzalez Sanchez
La realidad de la
gestión de
proyectos IA
CC BY 4.0 - Adrian Gonzalez Sanchez

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La realidad de la gestión de proyectos IA

  • 1. 16 diciembre 2021 Adrián González Sánchez La realidad de la gestión de proyectos IA CC BY 4.0 - Adrian Gonzalez Sanchez
  • 2. CC BY 4.0 - Adrian Gonzalez Sanchez [AI Lead Talk] La realidad de la gestión de proyectos IA x www.linkedin.com/in/adriangs86 https://adrian-gonzalezsanchez.medium.com 2 Vuestro amigo y vecino… Adrián González Sánchez Telco & IT Engineer, MSc. + MBA Tech Executive + University Lecturer Montreal, Canada _
  • 3. CC BY 4.0 - Adrian Gonzalez Sanchez [AI Lead Talk] La realidad de la gestión de proyectos IA Nuestro plan hoy - AI Lead Talk 2021 AI/ML Highlights – ¿Dónde estamos? Key Project Learnings – La realidad del día a día Q&A 3 1 2 3
  • 4. [AI Lead Talk] La realidad de la gestión de proyectos IA CC BY 4.0 - Adrian Gonzalez Sanchez 2021 AI/ML Highlights 4 1 I. Democratization of the AI adoption is generating new opportunities for all kinds of AI professionals (tech, biz, and hybrid profiles). I see more people with "atypical profiles" re/upskilling so they can help with new internal AI initiatives for small and medium businesses. We are going more granular in terms of AI skills and responsibilities. Cloud-enabled / aaS platforms are helping a lot. II. MLOps is the key industry trend, and an organic answer to the need for a well-defined end-to-end AI/ML lifecycle. This is also contributing to clarify tasks / micro-tasks and responsibilities. I think data and ML engineers will have a lot of fun in 2022 :) their roles are evolving very quickly, same as their importance within the adopter organizations. III. Responsible AI is finally becoming something tangible. Main concern for AI professionals was how to actually evaluate responsible AI factors during the analysis, implementation, and prod phases. Big companies are releasing both commercial and open source solutions to check fairness, explicability, data bias, etc. Still a WIP but I really like what I see from Microsoft, TensorFlow/Google, etc. IV. The data scientist skill set is also evolving. Some of the DS/DE tasks are becoming a bit more of a "commodity" (e.g., initial naive approaches, model benchmarking), and technical complexity requires more and better soft skills than ever. I have met wonderful data scientist, but my favourite ones are those who are able to explain choices and results in a very simple way, so everyone can understand the key pieces. Superstar data scientists will bring that to the companies, and they will become key decision influencers. Fuente propia: https://www.linkedin.com/posts/adriangs86_ai2021-2022predictions-ai-activity-6875764835808808961-RjnI
  • 5. [AI Lead Talk] La realidad de la gestión de proyectos IA CC BY 4.0 - Adrian Gonzalez Sanchez 5 The impact of early involvement of end-users in designing AI solutions 1 Key Project Learnings 2
  • 6. [AI Lead Talk] La realidad de la gestión de proyectos IA CC BY 4.0 - Adrian Gonzalez Sanchez 6 The benefits of AI education for stakeholders to facilitate adoption and collaboration 2 Key Project Learnings 2
  • 7. [AI Lead Talk] La realidad de la gestión de proyectos IA CC BY 4.0 - Adrian Gonzalez Sanchez 7 The importance of executive-level sponsorship and their understanding of AI 3 Key Project Learnings 2
  • 8. [AI Lead Talk] La realidad de la gestión de proyectos IA CC BY 4.0 - Adrian Gonzalez Sanchez 8 4 The incredible power of mission-oriented projects for AI implementations Key Project Learnings 2
  • 9. [AI Lead Talk] La realidad de la gestión de proyectos IA CC BY 4.0 - Adrian Gonzalez Sanchez 9 The notion of “good enough” AI model performance to manage expectations up-front 5 Key Project Learnings 2
  • 10. [AI Lead Talk] La realidad de la gestión de proyectos IA CC BY 4.0 - Adrian Gonzalez Sanchez 10 The trade-off between fully automated and HITL Human-in-the-loop systems 6 Key Project Learnings 2
  • 11. [AI Lead Talk] La realidad de la gestión de proyectos IA CC BY 4.0 - Adrian Gonzalez Sanchez 11 The necessity of using AI for specific “narrow” tasks and leveraging SME knowledge 7 Key Project Learnings 2
  • 12. [AI Lead Talk] La realidad de la gestión de proyectos IA CC BY 4.0 - Adrian Gonzalez Sanchez 12 The scalability of AI use cases and their connection with previous and future projects 8 Key Project Learnings 2
  • 13. [AI Lead Talk] La realidad de la gestión de proyectos IA CC BY 4.0 - Adrian Gonzalez Sanchez 13 The required effort for granular AI project planning and risk mitigation 9 Key Project Learnings 2
  • 14. [AI Lead Talk] La realidad de la gestión de proyectos IA CC BY 4.0 - Adrian Gonzalez Sanchez 14 The role of AI tooling and infrastructure to accelerate implementations 10 Key Project Learnings 2
  • 15. [AI Lead Talk] La realidad de la gestión de proyectos IA CC BY 4.0 - Adrian Gonzalez Sanchez 15 Mi regalo de navidad - Lecturas para gestión 360 de IA/ML +
  • 16. CC BY 4.0 - Adrian Gonzalez Sanchez [AI Lead Talk] La realidad de la gestión de proyectos IA 16 Q&A
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